The efficacy of anti-HIV drug therapy is often limited by the emergence of drug resistant mutant viruses and associated cross-resistance. The use of phenotypic and genotypic assays for the detection and quantitation of drug susceptibility is considered standard of care when designing drug regimens following prior regimen failure. However, the interpretive models used in resistance assays are still imperfect mainly because of the limited amount of clinical data available. The goal of this project is to develop the resources to fully exploit a unique database generated from the results of the clinical reference laboratory at ViroLogic, Inc. (South San Francisco, CA). Virologic maintains data from the phenotypic and genotypic resistance tests of over 15,000 HIV-l-infected patient samples. Analysis of data from the ViroLogic phenotype-genotype database, containing samples from patients of diverse origins and antiretroviral treatment exposure, can improve the reliability of findings related to frequencies and patterns of mutations associated with phenotypic drug resistance, and allow the definition of new resistance patterns. Development of tools to fully analyze this large (and growing) dataset is critical to improve the interpretation of genotype and phenotype results, and will also impact future drug development. The specific aims are: 1. Integrate phenotype and genotype data into a relational database for ad-hoc queries, comparison and analysis of data 2. Develop and implement resources for data annotation -assign HIV-1 subtype to genotypes -categorize the phenotype-genotype concordance and discordance type 3. Develop and implement resources for data filtering -wild-type viruses -genotype redundancy 4. Develop a toolbox of statistical and analytical approaches to improve genotypic interpretation algorithms (first application to ABC, TDF, 3TC, ddl, RTV-boosted IDV) The specific aims will be accomplished by constructing a new integrated database annotation tools for subtype, wild-type optimized for queries and search tools, designation, and type of phenotype-genotype con/discordance, and statistical evaluation of mutational variables and patterns associated with resistance to clinically important drugs with significant phenotype-genotype discordance.